This article has been reviewed according to Science X's editorial process and policies. Editors have highlighted the following attributes while ensuring the content's credibility: When university students set out to learn English as an additional language, it's not just about internalizing a new list of words; they also have to learn common word combinations. To sound fluent and natural, they'll need to say "strong wind" but not "muscular wind," or "reach a conclusion" but not "pull a conclusion"—a task that's particularly challenging for learners stepping into terminology-heavy academic fields from economics to engineering.
So what's the best way to learn those invaluable combinations, also known as collocations? According to a new paper from the UBC Sauder School of Business, data-driven learning, with a little boost from AI, is still the most reliable option. The findings are published in the journal Nouvelles perspectives en sciences sociales.
According to UBC Sauder lecturer Dr. Déogratias (Deo) Nizonkiza, the author of the study, the development of corpora—large, structured collections of texts and other language data—has been foundational for DDL approaches. It has happened in three major stages.
In 1961, a collection of texts called the Brown Corpus was developed at Brown University. It comprised 500 text samples from media, religion, fiction, science and other sources, each containing approximately 2,000 words. With roughly 1 million words, it represented the first large-scale collection of real-world American English, and it allowed researchers to effectively catalog and analyze the language and its use.
In the 1980s, as technology advanced and computing became more widely available, the concept of data-driven learning, or DDL, was introduced. Instead of memorizing phrases from textbooks, learners could access increasingly massive databases of texts—with word counts eventually exceeding 100 million—to discover everyday language patterns. In 2008 came the Corpus of Contemporary American English, or COCA—a 1 billion-word database that comprises nearly 500,000 texts from 1990 to 2019 and allows students not only to search for specific words but also to look for examples in different contexts and academic disciplines.
"That really significantly changed how we do things, specifically in the area of English for academic or professional purposes," Nizonkiza explains. "But the searches took so much time, and people would get discouraged." In addition to the sluggish searches, another stumbling block was that many language instructors didn't even know the corpora existed, let alone how to use them, and those who did often treated DDL as a secondary activity—not a core teaching tool. Now, with the advent of generative AI, or GenAI, Nizonkiza says the process of searching for collocations has become far faster and more familiar—but that doesn't mean educators should toss out the more traditional DDL approach.
Extract — continue reading at the source.
